python的reduce,lambda,和排序
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lambda用来编写简单的函数
lambda的使用方法如下:lambda arg1 ,arg2,arg3,...,argn : expression
fs = [(lambda n, i=i : i + n) for i in range(10)]
>>> fs[3](4)
7
>>> fs[4](4)
8
>>> fs[5](4)
9
filter
filter,map,reduce都是python的内建函数, filter与map较简单,都是对列表中值依次处理,输出结果也是列表。reduce则是依次把列别中的值两两作为参数,输入到函数中,结果未必是列表。
f>>> ilter(lambda x : x%2 == 0,[1,2,3,4,5])
[2, 4]
>>> map(lambda x : x * 2,[1,2,3,4,[5,6,7]])
[2, 4, 6, 8, [5, 6, 7, 5, 6, 7]]
reduce的实现
def reduce(bin_func,seq,initial=None):
lseq = list(seq)
if
initial is None:
res = lseq.pop(
0
)
else
:
res = initial
for
eachItem in lseq:
res = bin_func(res,eachItem)
return
res
>>> reduce(lambda x,y : x + y,[1,2,3,4])
10
>>> reduce(lambda x,y : x + y,[1,2,3,4],10)
20
另外注意:filter,map有时候可以被列表解析替代,而且列表解析更强大
a=[x*2 for x in range(10)]
a=[x for x in range(10) if x%3==0]
[x+y for x in range(5) if x%2 == 0 for y in range(10) if y%2 ==1] ,列表解析可以两层循环
list排序
list排序有两种方法,一是使用list的成员函数,二是使用内建函数sorted。
list的成员函数有3个参数list.sort(cmp=None, key=None, reverse=False)
三个参数的说明如下:
cmp:cmp specifies a custom comparison function of two arguments (iterable elements) which should return a negative, zero or positive number depending on whether the first argument is considered smaller than, equal to, or larger than the second argument:
"cmp=lambda x,y: cmp(x.lower(), y.lower())"
key:key specifies a function of one argument that is used to extract a comparison key from each list element: "key=str.lower"
reverse:reverse is a boolean value. If set to True, then the list elements are sorted as if each comparison were reversed.In general, the key and reverse conversion processes are much faster than specifying an
equivalent cmp function. This is because cmp is called multiple times for each list element while key and reverse touch each element only once.
cmp和key都是函数,
key是一个变量的函数,输入为list中的一个element,输出为一个可比较的element
cmp是两个边路的函数,输入为list重两个element,输出为这两个element的大小关系(大于0,小于0,等于0)
key与cmp往往不会同时使用
下面是使用例子:
实例1:
>>>L = [2,3,1,4]
>>>L.sort()
>>>L
>>>[1,2,3,4]
实例2:
>>>L = [2,3,1,4]
>>>L.sort(reverse=True)
>>>L
>>>[4,3,2,1]
实例3:
>>>L = [('b',2),('a',1),('c',3),('d',4)]
>>>L.sort(cmp=lambda x,y:cmp(x[1],y[1]))
>>>L
>>>[('a', 1), ('b', 2), ('c', 3), ('d', 4)]
实例4:
>>>L = [('b',2),('a',1),('c',3),('d',4)]
>>>L.sort(key=lambda x:x[1])
>>>L
>>>[('a', 1), ('b', 2), ('c', 3), ('d', 4)]
实例5:
>>>L = [('b',2),('a',1),('c',3),('d',4)]
>>>import operator
>>>L.sort(key=operator.itemgetter(1))
>>>L
>>>[('a', 1), ('b', 2), ('c', 3), ('d', 4)]
实例6:(DSU方法:Decorate-Sort-Undercorate)
>>>L = [('b',2),('a',1),('c',3),('d',4)]
>>>A = [(x[1],i,x) for i,x in enumerate(L)] #i can confirm the stable sort
>>>A.sort()
>>>L = [s[2] for s in A]
>>>L
>>>[('a', 1), ('b', 2), ('c', 3), ('d', 4)]
以上给出了6中对List排序的方法,其中实例3.4.5.6能起到对以List item中的某一项
为比较关键字进行排序.
效率比较:
cmp < DSU < key
通过实验比较,方法3比方法6要慢,方法6比方法4要慢,方法4和方法5基本相当
多关键字比较排序:
实例7:
>>>L = [('d',2),('a',4),('b',3),('c',2)]
>>> L.sort(key=lambda x:x[1])
>>> L
>>>[('d', 2), ('c', 2), ('b', 3), ('a', 4)]
我们看到,此时排序过的L是仅仅按照第二个关键字来排的,如果我们想用第二个关键字
排过序后再用第一个关键字进行排序呢?有两种方法
实例8:
>>> L = [('d',2),('a',4),('b',3),('c',2)]
>>> L.sort(key=lambda x:(x[1],x[0]))
>>> L
>>>[('c', 2), ('d', 2), ('b', 3), ('a', 4)]
实例9:
>>> L = [('d',2),('a',4),('b',3),('c',2)]
>>> L.sort(key=operator.itemgetter(1,0))
>>> L
>>>[('c', 2), ('d', 2), ('b', 3), ('a', 4)]
为什么实例8能够工作呢?原因在于tuple是的比较从左到右比较的,比较完第一个,如果
相等,比较第二个
====================================================================
python中pass含义:不做任何处理。
lambda用来编写简单的函数
lambda的使用方法如下:lambda arg1 ,arg2,arg3,...,argn : expression
fs = [(lambda n, i=i : i + n) for i in range(10)]
>>> fs[3](4)
7
>>> fs[4](4)
8
>>> fs[5](4)
9
filter
filter,map,reduce都是python的内建函数, filter与map较简单,都是对列表中值依次处理,输出结果也是列表。reduce则是依次把列别中的值两两作为参数,输入到函数中,结果未必是列表。
f>>> ilter(lambda x : x%2 == 0,[1,2,3,4,5])
[2, 4]
>>> map(lambda x : x * 2,[1,2,3,4,[5,6,7]])
[2, 4, 6, 8, [5, 6, 7, 5, 6, 7]]
reduce的实现
def reduce(bin_func,seq,initial=None):
lseq = list(seq)
if
initial is None:
res = lseq.pop(
0
)
else
:
res = initial
for
eachItem in lseq:
res = bin_func(res,eachItem)
return
res
>>> reduce(lambda x,y : x + y,[1,2,3,4])
10
>>> reduce(lambda x,y : x + y,[1,2,3,4],10)
20
另外注意:filter,map有时候可以被列表解析替代,而且列表解析更强大
a=[x*2 for x in range(10)]
a=[x for x in range(10) if x%3==0]
[x+y for x in range(5) if x%2 == 0 for y in range(10) if y%2 ==1] ,列表解析可以两层循环
list排序
list排序有两种方法,一是使用list的成员函数,二是使用内建函数sorted。
list的成员函数有3个参数list.sort(cmp=None, key=None, reverse=False)
三个参数的说明如下:
cmp:cmp specifies a custom comparison function of two arguments (iterable elements) which should return a negative, zero or positive number depending on whether the first argument is considered smaller than, equal to, or larger than the second argument:
"cmp=lambda x,y: cmp(x.lower(), y.lower())"
key:key specifies a function of one argument that is used to extract a comparison key from each list element: "key=str.lower"
reverse:reverse is a boolean value. If set to True, then the list elements are sorted as if each comparison were reversed.In general, the key and reverse conversion processes are much faster than specifying an
equivalent cmp function. This is because cmp is called multiple times for each list element while key and reverse touch each element only once.
cmp和key都是函数,
key是一个变量的函数,输入为list中的一个element,输出为一个可比较的element
cmp是两个边路的函数,输入为list重两个element,输出为这两个element的大小关系(大于0,小于0,等于0)
key与cmp往往不会同时使用
下面是使用例子:
实例1:
>>>L = [2,3,1,4]
>>>L.sort()
>>>L
>>>[1,2,3,4]
实例2:
>>>L = [2,3,1,4]
>>>L.sort(reverse=True)
>>>L
>>>[4,3,2,1]
实例3:
>>>L = [('b',2),('a',1),('c',3),('d',4)]
>>>L.sort(cmp=lambda x,y:cmp(x[1],y[1]))
>>>L
>>>[('a', 1), ('b', 2), ('c', 3), ('d', 4)]
实例4:
>>>L = [('b',2),('a',1),('c',3),('d',4)]
>>>L.sort(key=lambda x:x[1])
>>>L
>>>[('a', 1), ('b', 2), ('c', 3), ('d', 4)]
实例5:
>>>L = [('b',2),('a',1),('c',3),('d',4)]
>>>import operator
>>>L.sort(key=operator.itemgetter(1))
>>>L
>>>[('a', 1), ('b', 2), ('c', 3), ('d', 4)]
实例6:(DSU方法:Decorate-Sort-Undercorate)
>>>L = [('b',2),('a',1),('c',3),('d',4)]
>>>A = [(x[1],i,x) for i,x in enumerate(L)] #i can confirm the stable sort
>>>A.sort()
>>>L = [s[2] for s in A]
>>>L
>>>[('a', 1), ('b', 2), ('c', 3), ('d', 4)]
以上给出了6中对List排序的方法,其中实例3.4.5.6能起到对以List item中的某一项
为比较关键字进行排序.
效率比较:
cmp < DSU < key
通过实验比较,方法3比方法6要慢,方法6比方法4要慢,方法4和方法5基本相当
多关键字比较排序:
实例7:
>>>L = [('d',2),('a',4),('b',3),('c',2)]
>>> L.sort(key=lambda x:x[1])
>>> L
>>>[('d', 2), ('c', 2), ('b', 3), ('a', 4)]
我们看到,此时排序过的L是仅仅按照第二个关键字来排的,如果我们想用第二个关键字
排过序后再用第一个关键字进行排序呢?有两种方法
实例8:
>>> L = [('d',2),('a',4),('b',3),('c',2)]
>>> L.sort(key=lambda x:(x[1],x[0]))
>>> L
>>>[('c', 2), ('d', 2), ('b', 3), ('a', 4)]
实例9:
>>> L = [('d',2),('a',4),('b',3),('c',2)]
>>> L.sort(key=operator.itemgetter(1,0))
>>> L
>>>[('c', 2), ('d', 2), ('b', 3), ('a', 4)]
为什么实例8能够工作呢?原因在于tuple是的比较从左到右比较的,比较完第一个,如果
相等,比较第二个
====================================================================
python中pass含义:不做任何处理。
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